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Identifiability and estimation of recursive max‐linear models
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9781118619179openalex-snapshot
Structural Equations with Latent Variables
inferredcites →https://doi.org/10.1002/net.3230200503openalex-snapshot
Independence properties of directed markov fields
inferredcites →https://doi.org/10.1007/978-0-387-45024-7openalex-snapshot
Heavy-Tail Phenomena: Probabilistic and Statistical Modeling
inferredcites →https://doi.org/10.1007/978-0-387-75953-1openalex-snapshot
Extreme Values, Regular Variation and Point Processes
inferredcites →https://doi.org/10.1007/978-1-84996-299-5openalex-snapshot
Max-linear Systems: Theory and Algorithms
inferredcites →https://doi.org/10.1007/978-3-658-12153-2_8openalex-snapshot
Big Data: Progress in Automating Extreme Risk Analysis
inferredcites →https://doi.org/10.1007/s10651-006-0022-8openalex-snapshot
Spatial statistical models that use flow and stream distance
inferredcites →https://doi.org/10.1007/s10687-017-0303-7openalex-snapshot
A continuous updating weighted least squares estimator of tail dependence in high dimensions
inferredcites →https://doi.org/10.1016/0304-4149(89)90090-2openalex-snapshot
Estimation for first-order autoregressive processes with positive or bounded innovations
inferredcites →https://doi.org/10.1017/jpr.2016.37openalex-snapshot
One-component regular variation and graphical modeling of extremes
inferredcites →https://doi.org/10.1017/s0001867800019054openalex-snapshot
Basic properties and prediction of max-ARMA processes
inferredcites →https://doi.org/10.1201/9781420035988.ch2openalex-snapshot
Causal Inference from Graphical Models
inferredcites →https://doi.org/10.1214/aoms/1177728066openalex-snapshot
Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
inferredcites →https://doi.org/10.2307/2072165openalex-snapshot
Structural Equations with Latent Variables.
inferredcites →https://doi.org/10.2307/2530581openalex-snapshot
The Statistical Analysis of Failure Time Data.
inferredcites →https://doi.org/10.2307/3315231openalex-snapshot
Towards a unified definition of maximum likelihood
inferredcites →https://doi.org/10.3150/17-bej941openalex-snapshot
Max-linear models on directed acyclic graphs
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4640753openalex-extracted
Convergence Rate of Tail Dependence Function in Recursive Max-Linear Models on Directed Acyclic Graphs
inferred← citeshttps://doi.org/10.1002/cjs.70041openalex-snapshot
Causal analysis of extreme risk in a network of industry portfolios
inferred← citeshttps://doi.org/10.1007/978-3-030-26814-5_6openalex-snapshot
Bayesian Networks for Max-Linear Models
inferred← citeshttps://doi.org/10.1016/j.jmva.2020.104672openalex-snapshot
Estimating an extreme Bayesian network via scalings
inferred← citeshttps://doi.org/10.1016/j.jmva.2022.104999openalex-snapshot
Max-linear models in random environment
inferred← citeshttps://doi.org/10.1017/apr.2023.46openalex-snapshot
Max-linear graphical models with heavy-tailed factors on trees of transitive tournaments
inferred← citeshttps://doi.org/10.1080/01621459.2025.2595732openalex-snapshot
Principal Component Analysis for Max-Stable Distributions
inferred← citeshttps://doi.org/10.1093/jrsssb/qkad028openalex-snapshot
A model where the least trimmed squares estimator is maximum likelihood
inferred← citeshttps://doi.org/10.1093/jrsssb/qkad165openalex-snapshot
Estimating a directed tree for extremes
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11460823openalex-snapshot
Learning Directed Acyclic Graphs From Max-Times Structural Equation Models With Sparse Input
inferred← citeshttps://doi.org/10.1146/annurev-statistics-040620-041554openalex-snapshot
Sparse Structures for Multivariate Extremes
inferred← citeshttps://doi.org/10.1214/20-aos2021openalex-snapshot
Causal discovery in heavy-tailed models
inferred← citeshttps://doi.org/10.1214/21-aap1670openalex-snapshot
Conditional independence in max-linear Bayesian networks
inferred← citeshttps://doi.org/10.1214/21-ejs1903openalex-snapshot
Recursive max-linear models with propagating noise
inferred← citeshttps://doi.org/10.1214/25-aap2201openalex-snapshot
Graphical models for infinite measures with applications to extremes
inferred← citeshttps://doi.org/10.1214/25-ejs2469openalex-snapshot
Information criteria for the number of directions of extremes in high-dimensional data
inferred← citeshttps://doi.org/10.2140/astat.2021.12.213openalex-snapshot
Discrete max-linear Bayesian networks
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